Magic Ginis

If I were to stumble across a magic genie, I would not have to think hard about my three wishes. I would wish for my boyfriend to cut the animal rights crap and let me adopt a dog already. I would wish for the end of cars as personal transport, and I would also wish for something more magnanimous, like to end poverty now.

It’s easy to conceive of how poverty and good health usually don’t mesh. But social class affects health even for those who earn enough to afford good care and a health-promoting lifestyle. The Whitehall studies have shown among multiple cohorts of (not-impoverished) British government workers that a strong gradient persists between social class and a slew of health factors: mortality, disease incidence, and health-risk behaviors (smoking, diet, exercise).

But it’s not just you and your rung on the ladder, it’s where you live. In the U.S, research suggests that income inequality within a place affects the health of its residents (regardless of personal income) – at the state level and also within cities. One explanation for this may be that there is less social cohesion in places with more inequality – which has ramifications both for health and crime.

I wanted to take a closer look at recent patterns on income inequality across the U.S. In 2006 a new variable was reported on the American Community Survey: a Gini index that summarizes income inequality on a scale from 0 (perfect equality where all households have equal income) to 1 (perfect inequality – ie one household has 100% of the income of a state, census tract, etc). This magical gini index is based on the concept of the “Gini coefficient“, long used in economics to compare income distributions between geographies. It turns out that Gini is not an acronym (so after years of writing GINI I will stop), thanks Wikipedia!

From 2008-2010 ACS data, the most income-equal state was Alaska (Gini of 0.409) and the most unequal state was Washington DC (Gini of 0.533). Across states, the average GINI index value is 0.453.

Among the 866 urban areas with GINI data, the average value was slightly lower than among states, at 0.4467, with Charleston IL being the most unequal (GINI of 0.589) and Spanish Fork UT being the most equal (GINI of 0.320) – the urban areas with the 2nd and 3rd lowest GINIs are also in Utah.

Gini Index of States and Urban Areas across the U.S, 2008-2010 ACS

Static maps like this are.. okay. You can see that Gini indexes are highest in New York state and Connecticut (likely due to influence of New York City, comprising a good portion of these states’ working population and marked with higher incomes and cost of living), though you can’t clearly see that the District of Columbia has the highest Gini. There is also a cluster of relatively unequal (above-average Gini) states and urban areas in the Southeast. But wouldn’t it be great if you could zoom, and click on each city to see its name and corresponding Gini value?

Enter Google. A recent addition to Google’s suite of free utilities is Fusion Tables, which allows for databases to be linked to geographic features – KML files on a google map. This is very exciting because it means you can now do some things with Google Maps which beforehand were only possible with Geographic Information Systems like Arc, GRASS, and the like.

You can see the interactive “fusion map” version of the static map above, here:

Coming soon: a map of 5,200 foreclosed properties (and their assessed values) up for auction by the city this October in Buffalo NY. Real estate strategizing is in the air…


About katosulliv

Transportation, mapping, and cities enthusiast.
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